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Background  We evaluated the performance of a clinical algorithm (Expali ™),  combining two or more positive answers to SCOFF questionnaire with Body Mass Index (BMI), to identify four Broad Categories of eating disorders (ED) derived from DSM-5.    Methods  The clinical algorithm (Expali ™)  was developed from 104 combinations of BMI levels and answers to five SCOFF questions with at least two positive answers. Two senior ED physicians allocated each combination to one of the four Broad Categories of ED derived from DSM-5: restrictive disorder, bulimic disorder, hyperphagic disorder and other unspecified ED diagnosed by ED clinicians. The performance of Expali ™  was evaluated on data from 206 patients with ED. Sensitivity, specificity values and Youden index were calculated for each category.    Results  The 206 patients were diagnosed as follows: 31.5% restrictive disorder, 18.9% bulimic disorder, 40.8% hyperphagic disorder and 8.8% other ED. The sensitivity of Expali ™  for restrictive, bulimic, hyperphagic and other unspecified ED were respectively: 76.9, 69.2, 79.7 and 16.7%. The Youden index was respectively 0.73, 0.57, 0.67 and 0.07.    Conclusions  In a SCOFF-positive ED population (at least two positive answers), the clinical algorithm Expali ™  demonstrated good suitability by correctly classifying three of the four Broad Categories of eating disorders (restrictive, bulimic and hyperphagic disorder). It could be useful both to healthcare professionals and the general population to enable earlier detection and treatment of ED and to improve patient outcomes.

Screening four broad categories of eating disorders: suitability of a clinical algorithm adapted from the SCOFF questionnaire